Evidence map›Paper›PMID 40190681›Full record

ArticleAdvanced pharmaceutical bulletin2024

Mohadese Mirshekari, Azar Bagheri Ghomi, Hamed Hamishehkar, Mohammad Reza Farahpour

Abstract read
In one paragraph

Article in Advanced pharmaceutical bulletin, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mohadese MirshekariDepartment of Chemistry, Central Tehran Branch, Islamic Azad University, Tehran, Iran.ORCID https://orcid.org/0009-0006-0008-5114
Azar Bagheri GhomiDepartment of Chemistry, Central Tehran Branch, Islamic Azad University, Tehran, Iran.ORCID https://orcid.org/0000-0002-6696-3024
Hamed HamishehkarDrug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran.ORCID https://orcid.org/0000-0001-9905-0662
Mohammad Reza FarahpourDepartment of Clinical Sciences, Faculty of Veterinary Medicine, Urmia Branch, Islamic Azad University, Urmia, Iran.ORCID https://orcid.org/0000-0001-8631-071X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Medicinal plants and their derivatives have been used to treat wounds, and loading the plants into nanoliposomes (NLPs) helps to increase their efficacy. This study investigated the efficacy of NLPs loaded with Methods: In the present study, we thoroughly evaluated WHSE's antibacterial, antioxidant, and safety profiles. Additionally, we assessed wound contraction, pathological evaluations, and the expression of basic fibroblast growth factor (bFGF) and CD31. Results: The results showed that the extract and its NLPs had biocompatibility and exhibited antibacterial and antioxidant properties. Furthermore, our in vivo wound healing assay results showed that ointments containing 0.50% and 1.00% of the WHSE-NLPs accelerated wound healing and increased collagen and epithelialization. Furthermore, the results of the immunofluorescence and immunochemical tests indicated more expression of CD31 and bFGF in the mice that have been treated with WHSE-NLPs compared to those who were treated with WHSE and control groups. ( Conclusion: We demonstrated that the administration of 1.00% of the WHSE-NLPs could compete with the commercial ointment (Nitrofurazone®). Therefore, balms prepared from WHSE-NLPs expedited the wound healing process by increasing collagen, epithelialization, and the expression of CD31 and bFGF.

Indexed as

AngiogenesisAntibacterialAntioxidantEpithelializationNanoparticleWound healing

Identifiers

PMID40190681
PMCPMC11970498

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.